Mastering data structures and algorithms (DSA) is key to writing efficient code and solving complex problems. Python’s simplicity makes it a great language for learning and implementing core DSA concepts.

Essential data structures in Python:

• Lists – Dynamic arrays ([])
• Tuples – Immutable sequences
• Sets – Unordered collections with unique elements
• Dictionaries – Key-value mappings ({})

Advanced structures:

• Stacks & Queues – Use list, collections.deque
• Heaps – Use heapq for priority queues
• Linked Lists, Trees, Graphs – Implemented via classes and recursion

Key algorithms:

• Searching – Linear, Binary Search
• Sorting – Quick Sort, Merge Sort, Bubble Sort
• Recursion & Backtracking
• Graph Traversals – DFS, BFS
• Dynamic Programming – Memoization, Tabulation

Example: Binary Search

pythonКопироватьРедактироватьdef binary_search(arr, target):
    left, right = 0, len(arr)-1
    while left <= right:
        mid = (left + right)//2
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    return -1

Use platforms like LeetCode, HackerRank, or Codeforces to practice. DSA skills are essential for coding interviews, efficient software, and scalable systems.